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Chenxu Lv

dblp:297/4112 · DBLP profile ↗
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3ranked-venue papers
0as first author
3since 2021 · last 2026
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 2 since 2021Databases, data management, data science and information retrieval · 1 · 1 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Planning, search and constraint satisfaction · 56% Language models and text generation · 28% Question answering and dialogue systems · 16%

Topics — the 4 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning
agent planning
1.012026
DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints · ACL (1) 2026
Natural language and speech › Language models and text generation
LLM agents
1.012026
DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints · ACL (1) 2026
Knowledge, reasoning and agents › Planning, search and constraint satisfaction › planning
planning evaluation
1.012026
DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints · ACL (1) 2026
Natural language and speech › Question answering and dialogue systems
task-oriented dialogue
0.612022
A Low-Cost, Controllable and Interpretable Task-Oriented Chatbot: With Real-World After-Sale Services as Example · SIGIR 2022

Methods — techniques the papers use, named apart from their topics

tree-structured task flow · 0.6automatic dialogue construction · 0.6
YearPublicationVenuePosition
2026 DeepPlanning: Benchmarking Long-Horizon Agentic Planning with Verifiable Constraints
abstract
Yinger Zhang, Shutong Jiang, Renhao Li, Jianhong Tu, Yang Su, Lianghao Deng, Xudong Guo, ChenXu Lv, Junyang Lin. Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). 2026.
Yinger Zhang, Shutong Jiang, Renhao Li, Jianhong Tu, Lianghao Deng, Chenxu Lv, Junyang Lin
ACL (1)8
2022 A Low-Cost, Controllable and Interpretable Task-Oriented Chatbot: With Real-World After-Sale Services as Example
abstract
Though widely used in industry, traditional task-oriented dialogue systems suffer from three bottlenecks: (i) difficult ontology construction (e.g., intents and slots); (ii) poor controllability and interpretability; (iii) annotation-hungry. In this paper, we propose to represent utterance with a simpler concept named Dialogue Action, upon which we construct a tree-structured TaskFlow and further build task-oriented chatbot with TaskFlow as core component. A framework is presented to automatically construct TaskFlow from large-scale dialogues and deploy online. Our experiments on real-world after-sale customer services show TaskFlow can satisfy the major needs, as well as reduce the developer burden effectively.
Xiangyu Xi, Chenxu Lv, Yuncheng Hua, Wei Ye 0004, Chaobo Sun, Shuaipeng Liu, Fan Yang 0087, Guanglu Wan
SIGIR2
2021 Modeling Explicit Concerning States for Reinforcement Learning in Visual Dialogue
Zipeng Xu, Fandong Meng, Xiaojie Wang 0006, Duo Zheng, Chenxu Lv, Jie Zhou 0016
BMVC5